import numpy as np
import csv
import random
from datetime import datetime
from time import strftime


'''
Global and Local Empirical Bayes Smoothers with Gamma Model
'''

def getCurTime():
    """
    get current time
    Return value of the date string format(%Y-%m-%d %H:%M:%S)
    """
    format='%Y-%m-%d %H:%M:%S'
    sdate = None
    cdate = datetime.now()
    try:
        sdate = cdate.strftime(format)
    except:
        raise ValueError
    return sdate

def build_data_list(inputCSV):
    sKey = []
    fn = inputCSV
    ra = csv.DictReader(file(fn), dialect="excel")
    
    for record in ra:
        #print record[ra.fieldnames[0]], type(record[ra.fieldnames[-1]])
        for item in ra.fieldnames:
            temp = float(record[item])
            sKey.append(temp)
    sKey = np.array(sKey)
    sKey.shape=(-1,len(ra.fieldnames))
    return sKey



#--------------------------------------------------------------------------
#MAIN

if __name__ == "__main__":
    print "begin at " + getCurTime()


    filepath = 'C:/_DATA/migration89_08/COUNTY Migration/clean/temp/1.csv'

    output = []
    ra = csv.DictReader(file(filepath), dialect="excel")
    output.append(record)
    filepath = 'C:/_DATA/migration89_08/COUNTY Migration/clean/temp/2.csv'
    ra = csv.DictReader(file(filepath), dialect="excel")
    for record in ra:
        output.append(record)

    
    np.savetxt(filepath[:-4] + 'total.csv', output, delimiter=',', fmt = '%i')
    